• Support design and monitoring of EWA underwriting strategies and forecasting tools. • Translate analytical findings into clear recommendations for credit policies. • Support champion/challenger tests and experiment design for EWA risk strategies. • Assist in designing exposure limits, eligibility rules, and verification checks. • Query, clean, and analyze large bank transaction datasets using SQL and Python, or R/SAS). • Build dashboards, reports and durable data assets to track customer behavior and credit performance. • Perform EDA, feature engineering, and data quality checks to drive trusted insights. • Prepare model inputs, evaluate new data sources (including open-banking data), and track model performance. • Analyze performance of underwriting strategies and identify opportunities to improve accuracy and reduce losses. • Learn and introduce new analytical tools and techniques relevant to credit risk. • Partner with Product, Engineering, Data Science, and Operations to implement updates to policies and decisioning logic. • Support the coordination of initiatives with data suppliers. • Package insights into crisp narratives and presentations for stakeholders.